ReadyGPU TEE

Qwen: Qwen3.6 35B A3B

Model IDqwen/qwen3.6-35b-a3b

Qwen3.6-35B-A3B is an open-weight model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated attention. Served as a text-only TEE deployment via NEAR AI.

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input

$0.20/M

output

$1.27/M

context

262K

created

May 26, 2026

Supported API shape

input

text · image · video

output

text

tools

Not listed

json mode

Not listed

Verification

receipt

x-receipt-id

attestation

gateway report

session

attested upstream

provider

Phala

Provider

Phala

GPU TEE

input

$0.20/M

output

$1.27/M

context

262K

Performance comparison

Last 72h · UTC

$ pip install openai

1from openai import OpenAI
2import os
3
4MODEL = "qwen/qwen3.6-35b-a3b"
5
6client = OpenAI(
7    base_url="https://inference.phala.com/v1",
8    api_key=os.environ["PHALA_API_KEY"],
9)
10
11response = client.chat.completions.create(
12    model=MODEL,
13    messages=[{"role": "user", "content": "Run this privately."}],
14    extra_body={"provider": {"aci_verified": True}},
15)
16
17print(response.id)
18print(response.choices[0].message.content)

$ npm install openai

1import OpenAI from "openai"
2
3const MODEL = "qwen/qwen3.6-35b-a3b"
4
5const openai = new OpenAI({
6  baseURL: "https://inference.phala.com/v1",
7  apiKey: process.env.PHALA_API_KEY,
8})
9
10const response = await openai.chat.completions.create({
11  model: MODEL,
12  messages: [{ role: "user", content: "Run this privately." }],
13  provider: { aci_verified: true },
14})
15
16console.log(response.id)
17console.log(response.choices[0].message.content)

1curl https://inference.phala.com/v1/chat/completions \
2  -H "Authorization: Bearer $PHALA_API_KEY" \
3  -H "Content-Type: application/json" \
4  -d '{
5    "model": "qwen/qwen3.6-35b-a3b",
6    "messages": [
7      { "role": "user", "content": "Run this privately." }
8    ],
9    "provider": {"aci_verified": true}
10  }'

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